Position sensors are commonly used as input devices for computers, personal digital assistants (PDAs), media players, video game players, consumer electronics, cellular phones, payphones, point-of-sale terminals, automatic teller machines, kiosks and the like. One common type of sensor used in such applications is the touchpad-type sensor, which can be readily found, for example, as an input device on many notebook-type computers. A user generally operates the sensor by moving a finger, stylus or other stimulus near a sensing region of the sensor. The stimulus creates a capacitive, inductive or other electrical effect upon a carrier signal applied to the sensing region that can be detected and correlated to the position or proximity of the stimulus with respect to the sensing region. This positional information can in turn be used to move a cursor or other indicator on a display screen, or for any other purpose. One example of a touchpad-type position sensor that is based on capacitive sensing technologies is described in U.S. Pat. No. 5,880,411, which issued to Gillespie et al. on Mar. 9, 1999.
Although position sensors have been widely adopted for several years, designers continue to look for ways to improve the sensors' functionality and effectiveness. In particular, difficulties have long been realized in identifying and reducing the effects of noise upon the sensor. Noise originates from various sources, including computer display backlights, power supplies, wireless communication devices and the like. Although many sensors now include low and/or high-pass filters that can effectively remove many types of noise, problems remain in identifying and removing noise components with frequencies that are close to the sensor sensing frequency or any of its harmonics. So called “tuned noise” is difficult to identify or filter out because the effective “beat” frequency of the tuned noise is often very close to the frequency of signals resulting from the user-applied stimulus itself, causing the tuned noise to appear as a stimulus applied to the sensing region. As a result, distinguishing the effects of undesirable tuned noise from the desirable effects of the stimulus can be quite difficult. Further, the time to observe tuned noise can be significant because the beat frequencies of such noise can be relatively low (e.g. on the order of 10 Hz or less), and therefore the period of an entire beat cycle can be significant (e.g. on the order of ten seconds for a beat frequency of 0.1 Hz).
Nevertheless, several techniques for reducing the effects of tuned noise have been attempted. One conventional noise avoidance technique involves comparing the output signals produced by operating the sensor at two or more different sensing frequencies when no stimulus is present on the sensing region, and then subsequently operating the sensor using the frequency that produces the lesser amount of noise. This technique has several disadvantages, however, in that determining whether the stimulus is present at any given time can be difficult in practice, particularly in the presence of significant external noise. Moreover, because this technique measures noise only when the stimulus is not present, sources of noise present within the stimulus itself (e.g. environmental radio frequency noise coupled to the sensor via the stimulus) are not considered. Another technique for measuring tuned noise involves periodically disabling the sensing function to ensure that no stimulus is detected, and then comparing the noise levels observed at two or more different operating frequencies. While this technique does measure noise coupled to the sensor via the stimulus, it does not address the issue of low beat frequencies. Further, the complexities introduced by disabling the sensing function can be relatively difficult and/or expensive to implement in practice.
Accordingly, it is desirable to provide systems and methods for quickly, effectively and efficiently detecting noise in a position sensor, even when the frequency of the noise is close to the sensing frequency. Moreover, it is desirable to create a noise detection technique that is effective even when a stimulus is present at or near the sensing region. Other desirable features and characteristics will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background.